Inkfish Research Scientist in Machine Learning for Wearables
2 weeks ago Be among the first 25 applicants
About Us
The School of Life Course & Population Sciences is one of six Schools that make up the Faculty of Life Sciences & Medicine at King’s College London. The School unites over 400 experts in women and children’s health, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages, treating life, disease and healthcare as a continuum. We are interdisciplinary by nature and this innovative approach works: 91 per cent of our research submitted to the Subjects Allied to Medicine (Pharmacy, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments.
About Us
The School of Life Course & Population Sciences is one of six Schools that make up the Faculty of Life Sciences & Medicine at King’s College London. The School unites over 400 experts in women and children’s health, nutritional sciences, population health and the molecular genetics of human disease. Our research links the causes of common health problems to life’s landmark stages, treating life, disease and healthcare as a continuum. We are interdisciplinary by nature and this innovative approach works: 91 per cent of our research submitted to the Subjects Allied to Medicine (Pharmacy, Nutritional Sciences and Women's Health cluster) for REF was rated as world-leading or internationally excellent. We use this expertise to teach the next generation of health professionals and research scientists. Based across King’s Denmark Hill, Guy’s, St Thomas’ and Waterloo campuses, our academic programme of teaching, research and clinical practice is embedded across five Departments.
King’s College London is an internationally renowned university delivering exceptional education and world-leading research. We are dedicated to driving positive and sustainable change in society and realising our vision of making the world a better place. We are delighted to announce exciting new opportunities to join our community.
EMBRACE is a visionary, multicomponent International research programme, the first of its kind in the world, supported by Inkfish with £35M core funds over six years. It is a global study of 60,000 participants, including 20,000 mothers, 20,000 infants and up to 20,000 partners. It brings together world-leading clinician scientists across six distinguished Healthcare organisations, world-leading AI & technology companies, together with premier biotech companies, with the overarching aim to fast-track major scientific breakthroughs, revolutionise maternal and early childhood health through precision-personalised interventions, powered by a groundbreaking symbiosis of cutting-edge AI combined with human support.
About The Role
The Research Scientist in Machine Learning for Wearables will develop predictive deep learning models to assess maternal and partner health and behaviour throughout pregnancy, enabling a holistic understanding of health trajectories and personalised interventions. The post focuses on analysing multimodal data collected from wearable devices (e.g., heart rate, sleep patterns, physical activity) and voice biomarkers to identify patterns linked to maternal health outcomes. The goal is to support personalised health interventions and contribute to the advancement of precision maternal and early childhood care within the EMBRACE research programme, which is led by Professor Josip Car.
Multimodal wearable data will be collected from smartwatches/fitness trackers via continuously monitoring physiological metrics, including heart rate, heart rate variability, sleep patterns, physical activity levels, energy expenditure and so forth. They will be analysed to detect patterns and anomalies correlating with known markers of maternal health, including blood pressure, blood glucose, gestational weight gain, sleep and stress levels. In addition, the project will also aim to analyse voice biomarkers to capture unique vocal features that may reflect pregnant women’s physical and mental health risks and conditions. There will also be opportunities to develop research profile, travel for conferences and presentations, as well as contribute to academic publications.
The post holder is expected to hold a PhD degree in Bioinformatics, Computer Science or other relevant discipline. They will have skills in deep learning for wearable data analysis. Experience of studying health data science and/or machine learning for healthcare would be beneficial.
This is a full time post (35 hours per week), and you will be offered a fixed term contract until 31/08/2029.
About You
To be successful in this role, we are looking for candidates to have the following skills and experience:
Essential Criteria
- PhD in Bioinformatics, Computer Science or other closely related discipline *
- Experience in deep learning with a focus on predictive modelling for healthcare applications using wearable data (e.g., physical activity, heart rate, heart rate variability, sleep patterns)
- Sufficient breadth or depth of specialist knowledge in the discipline and of research methods and techniques to work within established research programmes
- Proficiency in signal processing and anomaly detection techniques to interpret physiological and behavioural data
- Research skills, as evidenced by a track record in high-quality academic journal publications and/or contributions to scientific conferences
- Good interpersonal skills, with evidence of networking across teams and complex organisation, along with external partners
- Ability to write research reports and papers accessible to both academic and lay audiences
- Project management skills - ability to initiate, plan, organise, implement and deliver programmes of work to tight deadlines
- Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.
Desirable criteria
- Knowledge of maternal health indicators, such as blood pressure, blood glucose, gestational weight gain, and stress assessment
- Ability or potential to contribute to the development of funding proposals in order to generate external funding to support research projects
Downloading a Copy Of Our Job Description
Full details of the role and the skills, knowledge and experience required can be found in the Job Description document, provided at the bottom of the next page after you click “Apply Now”. This document will provide information of what criteria will be assessed at each stage of the recruitment process.
Further Information
We pride ourselves on being inclusive and welcoming. We embrace diversity and want everyone to feel that they belong and are connected to others in our community.
We are committed to working with our staff and unions on these and other issues, to continue to support our people and to develop a diverse and inclusive culture at King's.
We ask all candidates to submit a copy of their CV, and a supporting statement, detailing how they meet the essential criteria listed in the advert. If we receive a strong field of candidates, we may use the desirable criteria to choose our final shortlist, so please include your evidence against these where possible.
To find out how our managers will review your application, please take a look at our ‘ How we Recruit’ pages.
We are able to offer sponsorship for candidates who do not currently possess the right to work in the UK.
This post is subject to Disclosure and Barring Service and Occupational Health clearances.
Grade and Salary:£44,355 to £51,735 per annum, including London Weighting Allowance
Job ID:117645
Close Date:14-Jul-2025
Contact Person:Prof Josip Car
Contact Details:Seniority level
- Seniority levelInternship
Employment type
Job function
- Job functionOther
- IndustriesHigher Education
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